Les questions de compétence internationale des tribunaux québécois soulevées par le recours collectif multi-juridictionnel : pragmatisme ou cohérence théorique

"Mémoire présenté à la Faculté des études supérieures en vue de l'obtention du grade de LL.M. en droit des affaires"

Développement d’une méthode de simulation multi-échelle pour l’étude des grandes transformations dans les protéines

Les films de simulations qui accompagnent le document ont été réalisés avec Pymol.

Development of a multi-gene PCR assay for the prediction of the response to hormone therapy in breast cancer

Deux tiers des cancers du sein expriment des récepteurs hormonaux ostrogéniques (tumeur ER-positive) et la croissance de ces tumeurs est stimulée par l’estrogène. Des traitements adjuvant avec des anti-estrogènes, tel que le Tamoxifen et les Inhibiteurs de l’Aromatase peuvent améliorer la survie des patientes atteinte de cancer du sein. Toutefois la thérapie hormonale n’est pas efficace dans toutes les tumeurs mammaires ER-positives. Les tumeurs peuvent présenter avec une résistance intrinsèque ou acquise au Tamoxifen. Présentement, c’est impossible de prédire quelle patiente va bénéficier ou non du Tamoxifen. Des études préliminaires du laboratoire de Dr. Mader, ont identifié le niveau d’expression de 20 gènes, qui peuvent prédire la réponse thérapeutique au Tamoxifen (survie sans récidive). Ces marqueurs, identifié en utilisant une analyse bioinformatique de bases de données publiques de profils d’expression des gènes, sont capables de discriminer quelles patientes vont mieux répondre au Tamoxifen. Le but principal de cette étude est de développer un outil de PCR qui peut évaluer le niveau d’expression de ces 20 gènes prédictif et de tester cette signature de 20 gènes dans une étude rétrospective, en utilisant des tumeurs de cancer du sein en bloc de paraffine, de patients avec une histoire médicale connue. Cet outil aurait donc un impact direct dans la pratique clinique. Des traitements futiles pourraient être éviter et l’indentification de tumeurs ER+ avec peu de chance de répondre à un traitement anti-estrogène amélioré. En conséquence, de la recherche plus appropriée pour les tumeurs résistantes au Tamoxifen, pourront se faire.

Study on acceleratore in rubber vulcanization with special reference to the binary systems containing substituted dithiobiurets

The thesis entitled Study on Accelerators in Rubber Vulcanization with Special Reference to the Binary Systems Containing Substituted Dithiobiurets. It includes a detailed study on the binary accelerator systems containing substituted dithiobiurets in natural rubber and NR latex and dithiobiurets in SBR and NR-SBR blends vulcanization systems. It deals with the experimental procedure adopted for the preparation of DTB-II and DTB-III; the procedure for compounding and vulcanization and determination of physical properties like modulus, tensile strength, elongation at break, hardness, compression set, heat build up etc. The results indicate that there is efficient acceleration activity of the dithiobiurets in the vulcanization of natural rubber latex containing TMT. The study of dithiobiurets in natural rubber and NR latex reveal that they are having definite accelerating effect in SBR vulcanization systems.

PERFORMANCE OF DIFFERENT CLASSIFIERS IN SPEECH RECOGNITION

Speech is the most natural means of communication among human beings and speech processing and recognition are intensive areas of research for the last five decades. Since speech recognition is a pattern recognition problem, classification is an important part of any speech recognition system. In this work, a speech recognition system is developed for recognizing speaker independent spoken digits in Malayalam. Voice signals are sampled directly from the microphone. The proposed method is implemented for 1000 speakers uttering 10 digits each. Since the speech signals are affected by background noise, the signals are tuned by removing the noise from it using wavelet denoising method based on Soft Thresholding. Here, the features from the signals are extracted using Discrete Wavelet Transforms (DWT) because they are well suitable for processing non-stationary signals like speech. This is due to their multi- resolutional, multi-scale analysis characteristics. Speech recognition is a multiclass classification problem. So, the feature vector set obtained are classified using three classifiers namely, Artificial Neural Networks (ANN), Support Vector Machines (SVM) and Naive Bayes classifiers which are capable of handling multiclasses. During classification stage, the input feature vector data is trained using information relating to known patterns and then they are tested using the test data set. The performances of all these classifiers are evaluated based on recognition accuracy. All the three methods produced good recognition accuracy. DWT and ANN produced a recognition accuracy of 89%, SVM and DWT combination produced an accuracy of 86.6% and Naive Bayes and DWT combination produced an accuracy of 83.5%. ANN is found to be better among the three methods.

An Efficient Multi-component Synthesis of 6-Amino-3-methyl-4-Aryl-2,4- dihydropyrano[2,3-c]Pyrazole-5-carbonitriles

Multi-component reactions are effective in building complex molecules in a single step in a minimum amount of time and with facile isolation procedures; they have high economy1–7 and thus have become a powerful synthetic strategy in recent years.8–10 The multicomponent protocols are even more attractive when carried out in aqueous medium. Water offers several benefits, including control over exothermicity, and the isolation of products can be carried out by single phase separation technique. Pyranopyrazoles are a biologically important class of heterocyclic compounds and in particular dihydropyrano[2,3-c]pyrazoles play an essential role in promoting biological activity and represent an interesting template in medicinal chemistry. Heterocyclic compounds bearing the 4-H pyran unit have received much attention in recent years as they constitute important precursors for promising drugs.11–13 Pyrano[2,3-c]pyrazoles exhibit analgesic,14 anti-cancer,15 anti-microbial and anti-inflammatory16 activity. Furthermore dihydropyrano[2,3-c]pyrazoles show molluscidal activity17,18 and are used in a screening kit for Chk 1 kinase inhibitor activity.19,20 They also find applications as pharmaceutical ingredients and bio-degradable agrochemicals.21–29 Junek and Aigner30 first reported the synthesis of pyrano[2,3-c]pyrazole derivatives from 3-methyl-1-phenylpyrazolin-5-one and tetracyanoethylene in the presence of triethylamine. Subsequently, a number of synthetic approaches such as the use of triethylamine,31 piperazine,32 piperidine,33 N-methylmorpholine in ethanol,34 microwave irradiation,35,36 solvent-free conditions,37–39 cyclodextrins (CDs),40 different bases in water,41 γ -alumina,42 and l-proline43 have been reported for the synthesis of 6-amino-4-alkyl/aryl-3-methyl- 2,4-dihydropyrano[2,3-c]pyrazole-5-carbonitriles. Recently, tetraethylammonium bromide (TEABr) has emerged as mild, water-tolerant, eco-friendly and inexpensive catalyst. To the best of our knowledge, quaternary ammonium salts, more specifically TEABr, have notbeen used as catalysts for the synthesis of pyrano[2,3-c]pyrazoles, and we decided to investigate the application of TEABr as a catalyst for the synthesis of a series of pyrazole-fused pyran derivatives via multi-component reactions

A Note on the Generalization Performance of Kernel Classifiers with Margin

We present distribution independent bounds on the generalization misclassification performance of a family of kernel classifiers with margin. Support Vector Machine classifiers (SVM) stem out of this class of machines. The bounds are derived through computations of the $V_gamma$ dimension of a family of loss functions where the SVM one belongs to. Bounds that use functions of margin distributions (i.e. functions of the slack variables of SVM) are derived.

Comparing Support Vector Machines with Gaussian Kernels to Radial Basis Function Classifiers

The Support Vector (SV) machine is a novel type of learning machine, based on statistical learning theory, which contains polynomial classifiers, neural networks, and radial basis function (RBF) networks as special cases. In the RBF case, the SV algorithm automatically determines centers, weights and threshold such as to minimize an upper bound on the expected test error. The present study is devoted to an experimental comparison of these machines with a classical approach, where the centers are determined by $k$--means clustering and the weights are found using error backpropagation. We consider three machines, namely a classical RBF machine, an SV machine with Gaussian kernel, and a hybrid system with the centers determined by the SV method and the weights trained by error backpropagation. Our results show that on the US postal service database of handwritten digits, the SV machine achieves the highest test accuracy, followed by the hybrid approach. The SV approach is thus not only theoretically well--founded, but also superior in a practical application.

Enhanced multi-layer protection in multi-service GMPLS networks

This paper focuses on QoS routing with protection in an MPLS network over an optical layer. In this multi-layer scenario each layer deploys its own fault management methods. A partially protected optical layer is proposed and the rest of the network is protected at the MPLS layer. New protection schemes that avoid protection duplications are proposed. Moreover, this paper also introduces a new traffic classification based on the level of reliability. The failure impact is evaluated in terms of recovery time depending on the traffic class. The proposed schemes also include a novel variation of minimum interference routing and shared segment backup computation. A complete set of experiments proves that the proposed schemes are more efficient as compared to the previous ones, in terms of resources used to protect the network, failure impact and the request rejection ratio

How to get the Reform in the English class room. 'Cómo conseguir la Reforma en el aula de Inglés'.

Documento que recoge la experiencia del profesorado perteneciente al grupo de trabajo de Lengua Extranjera Inglesa de Bachillerato LOGSE durante los dos primeros años de su experimentación en la Comunidad Autónoma del País Vasco. Se presentan los instrumentos utilizados para la evaluación inicial, los materiales utilizados en el aula, y los criterios para evaluar el proceso de aprendizaje de los alumnos, así como los resultados de esta evaluación. Se describe el proceso de introducción del aprendizaje autónomo y de los proyectos de trabajo como método para la introducción del Diseño Curricular Base en el aula, así como la experiencia de intercambio de alumnado con un centro americano de Educación Secundaria, realizado gracias a la concesión de una beca por la Diputación Foral de Bizkaia y a los contactos mantenidos entre el profesorado de ambos centros. Se recoge, también, la revisión que se realizó, tanto de la metodología como de los materiales utilizados en el aula. Por último, tras una introducción teórica sobre los proyectos de trabajo, se describe con detalle el proyecto de elaboración de una revista escolar. El grupo hace una autoevaluación muy positiva del trabajo realizado y del apoyo con que han contado tanto para llevarlo a cabo como para su propia formación.

Supporting students with dyslexia in secondary schools : every class teacher's guide to removing barriers and raising attainment.

El manual se centra en la enseñanza y el aprendizaje de los estudiantes con dislexia en la escuela secundaria y proporciona orientación práctica para los directores y profesores. Pone de relieve los obstáculos que tienen los estudiantes disléxicos en el currículo de hoy. Da información sobre cómo influye la dislexia en el acceso y el progreso de los estudiantes en la enseñanza secundaria, cómo los profesores pueden minimizar estas barreras identificando posibles obstáculos en el aprendizaje, las estrategias de apoyo para las resoluciones de las necesidades y elevar el logro de los estudiantes disléxicos.

A Multi Bearer Adaptable Communication Demonstrator for Train-to-Ground IP Communication to Increase Resilience

Preprint version